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g2p

G2P is an integrated genomic selection (GS) package for predicting phenotypes from genotypes. It includes 15 GS algorithms and 13 evaluation measurements.

gcforest

This is the official implementation for the paper 'Deep forest: Towards an alternative to deep neural networks'

gcn

Implementation of Graph Convolutional Networks in TensorFlow

gcn_metric_learning

Metric Learning with Graph Convolutional Neural Networks

gcn_tf

Graph Convolutional Networks Examples using TensorFlow

gda

Generalized Discriminant Analysis (GDA) - non-linear feature dimensionality reduction technique

gdlibrary

Matlab library for gradient descent algorithms: Version 1.0.0

gene_regulatory_network_modeling

MATLAB source code for Jang et al. paper, "Dynamics of embryonic stem cell differentiation inferred from single-cell transcriptomics show a series of transitions through discrete cell states."

generalizedpca

Dimensionality reduction for exponential family data by extending PCA

generative-models

Collection of generative models, e.g. GAN, VAE in Pytorch and Tensorflow.

geomstats

Computations and statistics on manifolds with geometric structures.

getting-started-ml.github.io

A community-driven place to get started with machine learning and AI.

ggplot2-book

The ggplot2 book

gini-pca

Robust L1 PCA based on the Gini metric

giniclust

GiniClust: Detecting Rare Cell Types from Single-Cell Gene Expression Data with Gini Index

gluon-api

A clear, concise, simple yet powerful and efficient API for deep learning.

gluon-tutorials-zh

通过MXNet/Gluon来动手学习深度学习

gnnpapers

Must-read papers on graph neural network (GNN)

good-papers

I try my best to keep updated cutting-edge knowledge in Machine Learning/Deep Learning and Natural Language Processing. These are my notes on some good papers

gosta

grabcut_annotation_tool

Semi-automatic segmentation of an object in a video sequence or a single image using Grabcut alg.

gradient-descent

Gradient Descent and Logistic Regression

gradient-descent-logistic-regression

An assignment using Matlab to perform logistic regression using gradient descent. I wrote the gradient descent algorithm.

graph-based-deep-learning-literature

links to conference publications in graph-based deep learning

graph-multi-nmf-feature-clustering

Feature Extraction via Multi-view Non-negative Matrix Factorization with Local Graph Regularization.

graph-networks

A list of interesting graph neural networks (GNN) links with a primary interest in recommendations and tensorflow that is continually updated and refined

graph-neural-networks

graphconvolutionalnetwork

Implementation of graph convolutional networks for classification in knowledge graphs

graphhopper-kernels

Scalable kernels for graphs with continuous attributes (Feragen et al., NIPS 2013) http://goo.gl/VxSfzZ

graphkernels